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Consider curves that pass through the origin and have the required property that f(x)\times\frac{df(x)}{dx} \leq 0
Suppose f(x) is positive for some positive x=x_0. If we require f(0)=0, this means the gradient must be positive for part of the interval [0, x_0], which would mean that f(x)\times\frac{df(x)}{dx} > 0 for these points.
Similarly, if we suppose f(x) is negative for some positive x=x_0, we find that the gradient will have to be negative for part of the interval [0,x_0], which would mean that f(x)\times\frac{df(x)}{dx} > 0 for these points.
We therefore need f(x)\equiv0 for all x\ge0.
For x< 0, we can choose f so that f(x)\not\equiv0. For example, we can choose f to be positive but have a negative gradient for all x< 0, which would mean f(x)\times\frac{df(x)}{dx} < 0.
Let's try choosing f=-x for x< 0:
This satisfies the condition f(x)\times\frac{df(x)}{dx} \leq 0 for all x. The other condition was that the derivative exists for all x. For x> 0, \frac{df(x)}{dx} = 0, and for x< 0, \frac{df(x)}{dx}=1. However, what's the derivative at x=0? As we approach from the right, \frac{df(x)}{dx}=1, but as we approach from the left, \frac{df(x)}{dx}=0. Therefore, our derivative doesn't exist at x=0 as was required, so we need to think of something else! (For a rigorous treatment of this, see a first year analysis course.)
We need to think of another function with behaviour like the previous one, but with a gradient of 0 as we approach x=0. Let's try the next simplest polynomial, a quadratic: f(x) = x^2. This passes through the origin, and has derivative \frac{df(x)}{dx}=2x. So at x=0, the derivative is 0 as we approach from both directions, so therefore exists. We've found a function that has the desired properties!
If we don't have the requirement that f(0)=0, there are lots of examples, e.g. f(x)=exp(-x).
Here, f(x)>0 for all x, and the gradient exists for all x and is negative: \frac{df(x)}{dx} = -exp(-x) <0, as required.
Can you massage the parameters of these curves to make them match as closely as possible?